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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: PegasusMedicalSummary |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# PegasusMedicalSummary |
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### Authors |
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This model was created by [renegarza](https://huggingface.co/renegarza) and [mereshd](https://huggingface.co/mereshd). |
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This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1438 |
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- Rouge1: 0.4318 |
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- Rouge2: 0.2525 |
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- Rougel: 0.3524 |
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- Rougelsum: 0.3525 |
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- Gen Len: 55.882 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 6.5172 | 1.0 | 999 | 0.1784 | 0.4161 | 0.2373 | 0.3388 | 0.3384 | 52.102 | |
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| 0.3174 | 2.0 | 1999 | 0.1550 | 0.4236 | 0.2434 | 0.343 | 0.3428 | 54.458 | |
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| 0.2632 | 3.0 | 2999 | 0.1462 | 0.4269 | 0.2467 | 0.3465 | 0.3464 | 55.503 | |
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| 0.2477 | 4.0 | 3996 | 0.1438 | 0.4318 | 0.2525 | 0.3524 | 0.3525 | 55.882 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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